Till Rohrmann created FLINK-1729:
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Summary: Assess performance of classification algorithms
Key: FLINK-1729
URL: https://issues.apache.org/jira/browse/FLINK-1729
Project: Flink
Issue Type: Improvement
Components: Machine Learning Library
Reporter: Till Rohrmann
In order to validate Flink's classification algorithms (in terms of performance
and accuracy), we should run them on publicly available classification data
sets. This will not only serve as a proof for the correctness of the
implementations but will also show how easy the machine learning library can be
used.
Bottou [1] published some results for the RCV1 dataset using SVMs for
classification. The SVMs are trained using stochastic gradient descent. Thus,
they would be a good comparison for the CoCoA trained SVMs.
Resources:
[1] [http://leon.bottou.org/projects/sgd]
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